Causes of capelin stock fluctuations

Photo, Frederik Broms, NPI.

Interactions, drivers and pressures 2019
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The Barents Sea capelin has undergone dramatic changes in stock size over the last four decades. Three stock collapses (when abundance was low and fishing moratoriums imposed) occurred during 1985–1989, 1993–1997, and 2003–2006. During the recent period 2014-2019 the stock estimates have fluctuated considerably. A rapid decline in stock size was recorded from 2014 onwards, and in 2016 the lowest biomass of capelin since 2005 was estimated from the joint Russian-Norwegian autumn Barents Sea Ecosystem Survey (BESS).

Causes of capelin stock fluctuations

Stock size fluctuations

The capelin stock size estimate from 2017, however, contrasted the two previous years and was so much higher that the results from 2016 and 2017 were incompatible when comparing cohorts (Skaret et al., 2019). For several reasons, the Arctic Fisheries Working Group concluded in 2017 that the 2017 survey was the more reliable of the two. Skaret et al. (2019) came to the same conclusion after having considered several possible reasons for either an underestimate in 2016 or an overestimate in 2017. Observations from the fisheries in 2018 and the autumn acoustic estimate of capelin in 2018, which was in line with the survey in 2017, strengthened this conclusion. However, the stock size estimate in autumn 2019 found the stock to be in very bad shape. It is unreasonable that the natural mortality should change so much from year to year, and one may question whether the surveys in recent years have given a reliable picture of the real trends in stock size. No firm conclusions can be drawn before one or more additional years of stock estimates have been added to the time series. Previous collapses have had serious effects both up and down the foodweb. Reduced predation pressure from capelin has led to increased amounts of zooplankton during periods of capelin collapse. When capelin biomass was drastically reduced, its predators were affected in various ways. Cannibalism became more frequent in the cod stock, cod growth was reduced, and maturation delayed. Seabirds experienced increased rates of mortality, and total recruitment failures; breeding colonies were abandoned for several years. Harp seals experienced food shortages, and recruitment failure, and increased mortality; partly because they invaded coastal areas and were caught in fishing gear. The effects were most serious during the 1985–1989 collapse, whereas, the effects could hardly be traced during the third collapse. Gjøsæter et al. (2009) concluded that these differences in effect likely resulted from increased availability of alternative food sources during the second and third collapses (1990s and 2000s). These collapses were caused by poor recruitment, most likely in combination with low growth and increased predation pressure. It is likely that high levels of fishing pressure during 1985–1986 amplified and prolonged the first collapse. After each collapse, the fishery has been closed and the stock has recovered within a few years due to good recruitment. Several authors have suggested that predation by young herring on capelin larvae has had a strong negative influence on capelin recruitment and, thus, has been a significant factor contributing to these capelin collapses (Gjøsæter et al., 2016), while others (Dolgov et al., 2019) claim that other reasons for the periodic recruitment failures could be more important.

Recruitment of capelin and polar cod

Capelin is a short-lived species and thus the stock size variation is strongly influenced by the annual recruitment variability. This may indicate that the main reason of capelin stock collapses is poor recruitment (Figure 4.3.1). There was a better correspondence between the abundance of 0-group and one-year-olds in the first half of the time period where both estimates are available. In recent years, very high but fluctuating estimates of 0-group were obtained and the mortality from age 0 to age 1 has seemingly increased. Especially the year classes 2007-2010, 2012-2013 and 2016-17 were heavily reduced in size from the 0-group to the 1-group stage. While the three first capelin stock collapses were initiated by increased mortality at the early larval stage, between the larval survey in May-June and the 0-group survey in August, the increased mortality on young capelin in recent years is seemingly occurring later; between the 0-group survey and the acoustic measurement of the 1-year-olds. The reasons for this seemingly increased natural mortality at this stage is unknown but could likely be caused by other factors than those in effect during the collapses in the 1980s, the 1990s, and the 2000s.

Figure 4.3.1. Fluctuation of capelin at age 0 (red line) and 1 (blue line) for the cohorts 1980–2019. Figure 4.3.1. Fluctuation of capelin at age 0 (red line) and 1 (blue line) for the cohorts 1980–2019.

Mean length of 0-group capelin has varied somewhat during the data time-series. From a biological perspective, one may hypothesize that survival rates from age 0 to age 1 might be correlated with lengths-at-age 0. However, a plot of mean length-at-age 0 and total mortality, from age 0 to age 1, shows no such correlation; rather, this plot shows that 0-group and/or 1-group abundance estimates and, therefore also, mortality estimates from age 0 to age 1, are noisy; this could possibly mask possible relationships that might exist. Figure 4.3.2 shows a stock–recruitment plot (updated from Gjøsæter et al. (2016)) for the year classes 1973-2018. The SSBs are those estimated by the assessment model for capelin (ICES 2019a). The points are coloured according to the amount of young herring estimated to be in the Barents Sea in the spawning year. Prior to 1991 the amount of herring is the abundance of age 1 and age 2 herring from the assessment model times the mean weight of these age groups; from 1991 it is the acoustic biomass estimate from herring survey in the Barents Sea in summer (ICES 2019b). The 1989-year class is the strongest year class at age 1 (700 billion). The average recruitment in the period is about 180 billion. It is seen that the recruitment in “red years” are below average recruitment in 11 out of 12 years, while in “green years” the recruitment is below average in 7 out of 12 years. In years with low numbers of young herring in the Barents Sea the recruitment is below average in 10 out of 22 years. This supports the hypothesis that capelin recruitment is negatively affected in years with substantial amounts of young herring in the Barents Sea (Gjøsæter et al. 2016). On the other hand, the general shape of the stock-recruitment relationship, where the highest recruitment is obtained for small to medium SSBs, points to the possibility of cannibalism or other density dependent mortality mechanisms (Dolgov et al., 2019). In any case, the large variability in recruitment clearly indicates an interplay of many factors affecting the recruitment of capelin.

Figure 4.3.2. SSB/R plot for capelin. Cohorts 1973–2018. Points coded according to herring biomass as explained in the text. (Updated from Figure 7 in Gjøsæter et al. 2016). Figure 4.3.2. SSB/R plot for capelin. Cohorts 1973–2018. Points coded according to herring biomass as explained in the text. (Updated from Figure 7 in Gjøsæter et al. 2016).

Figure 4.3.3 depicts a stock-recruitment plot based on maturing stock size during autumn ½ a year before spawning instead of estimated spawning stock size, and estimated number of 0-group capelin as an indicator of recruitment instead of one-year-olds.

Figure 4.3.3. Relationship between mature stock biomass (>14 cm) with spring fishery subtracted (biomass at 1 Oct. Y, total landings from 1 January to 1 April.Y+1 are subtracted, 1000 tonnes) and 0-group index in billions (Y+1), covering the cohorts 1980–2019. The size of bubbles indicates the biomass of herring at age 1-3 (ICES WGIBAR data). Minimum diameter of bubble corresponds to 0.02 million tonnes of herring (1983), the maximum ¬ - 5.02 million tonnes. (1994). The red point ¬is the 1989 cohort which is the basis for the current reference point (Blim). Figure 4.3.3. Relationship between mature stock biomass (>14 cm) with spring fishery subtracted (biomass at 1 Oct. Y, total landings from 1 January to 1 April.Y+1 are subtracted, 1000 tonnes) and 0-group index in billions (Y+1), covering the cohorts 1980–2019. The size of bubbles indicates the biomass of herring at age 1-3 (ICES WGIBAR data). Minimum diameter of bubble corresponds to 0.02 million tonnes of herring (1983), the maximum ¬ - 5.02 million tonnes. (1994). The red point ¬is the 1989 cohort which is the basis for the current reference point (Blim).

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